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Leveraging knowledge in a data rich world - Big Data and Business Analytics

We all heard about “big data”; which is incomprehensibly large data generated by real people. To give you an idea of scale; 90% of all data was created in the last 2 years, and we currently generate c. 2.5 quintillion bytes of data a day. Large volumes of data bring challenges to business; how to process such incomprehensibly large datasets to extract real value? And what does this mean for an enterprise in Malta which owns such data?

Business intelligence (BI) is an umbrella term that covers architectures, tools, databases, analytical tools, applications, and methodologies. To generate real value from the data, you can start by asking yourself;

  • Am I able to achieve an objective or a goal by using big data analysis?
  • Can I do something more with the data I have (i.e. secondary use)?

The challenge of having these questions answered for the Maltese business is usually a circular problem: (1) lack of resources to effectively use BI to answer the questions above, and (2) lack of scale to be able to have resources in place to be able to answer such questions. We can explore solutions and ways to scale upwards once you start building value later in this paper.

First let’s look at some examples where organisations started adding value:

  1. Objective-driven: I was personally part of a programme management team for a Know Your Customer (KYC) remediation project in a tier 1 bank in UK. Our aim was to reduce information requests to customers by gathering data that can inform us of the Anti-Money-Laundering (AML) risk by combining data to form a detailed profile of the customer. The data that we went for included the average salary per post code; that information by itself may be redundant; but when combined with other data, it provides granular data on the customer that could reduce the need for information requests.
  2. Data-driven: The intra-bank payment gateway system; SWIFT, found that their transaction data which they keep for audit and traceability purposes, correlates with regional and national GDP growth data. SWIFT realized they can analyse the data they hold to produce reliable leading GDP indicators.

Why is this relevant?

Firstly, and most important; you want to remain relevant in your market; examples like the rise and fall of Kodak and Nokia show us how lack of adaptability can quickly make you irrelevant in a market, even if you are the innovator in that market.

In a survey by (Dresner Advisory Services, LLC, 2017)[1], the authors found that SMEs are the most prevalent users of BI. The reason may be the use of scalable cloud technologies that empowers SMEs. In fact, more than 25% of SMEs with 1-100 employees have mastered BI and use it to automate 80% or more of the reports they issue. This shows that SMEs worldwide are using BI already, and have found ways to evolve its use to add value. There are no such local studies to explore the prevalence of BI, but based on our view of the local market, there is a lack of use for such tools. Main reasons being:

  • Data collation stage is not integrated; I have seen cases where data on transactions and stock is hosted by a franchise and not used locally
  • Lack of data warehousing capability; no joined-up offline data interrogation capability
  • No real data automation; most management accounts seem to be done manually, and there are no automated checks alerting users as issues occur.
  • Lack of efficient stock management
  • Outdated systems that rely on IT departments to hold them together with regular manual data inputs

What should be my ultimate objective?

Your ultimate objective is to be able to have a system which you are continuously improving to maximise the marginal benefits that you can obtain. This point in the curve is hard to achieve in a “micro” economy like ours – in Malta we lack the scale that can be achieved in larger countries. However, new BI tools and cloud technology have made it accessible to all types of enterprise to start analysing big data without having an expensive IT setup.

How can I start working towards that?

We always advocate to tread water and make continuous improvements to achieve all the marginal benefits obtainable from automating most / some / all of your reporting mechanisms. A picture says a thousand words; actually generating real value by showing a management accounting dashboard such as an automated income statement report will prove your case for more investment into BI to eliminate repetitive tasks. This will free resource to focus on more value adding tasks.

How can we help you

At Grant Thornton we started to use a host of different tools that can help your business get value from data. Our services range from consulting, to hosting management information (including management accounts) that are automatically reconciled and updated periodically.

We understand that each organisation is different; having a conversation about how to tailor your approach to start analysing data will help you generate ideas, and if our services are not right for you, we will guide you and suggest next steps.



[1] Dresner Advisory Services, LLC. (2017). 2017 Small and Mid-Sized Enterprise Business Intelligence Market Study. Dresner Advisory Services, LLC.